All rights reserved. Data-driven educational decision making refers to the process by which educators examine assessment data to identify student strengths and deficiencies and apply those findings to their practice. More recently researchers have studied how children evaluate evidence in the context of self-directed experimental tasks.
Reminiscent of the results of the earlier study by Kuhn and Phelps, both children and adults display intraindividual variability in strategy usage. There is an extensive literature on the evaluation of evidence, beginning with early research on identifying patterns of covariation and cause that used highly structured experimental tasks. The ecologist could then predict that regardless of how early spring comes, the birds and their insect prey will always be somewhat synchronized in time.
You measure the effect this has on the dependent variable. Confounded experiments, those in which variables have not been isolated correctly, yield indetermi- Page Share Cite Suggested Citation:"5 Generating and Evaluating Scientific Evidence and Explanations. She had her students analyze several small tomato plants she had grown and record their observations.
Empirical research is the process of finding empirical evidence. For example, some emphasize the design of well-controlled experiments, while others emphasize building and critiquing models of natural phenomena. The strength of any scientific research depends on the ability to gather and analyze empirical data in the most unbiased and controlled fashion possible. When working in the science context, the children worked more systematically, by establishing the effect of each variable, alone and in combination.
With respect to attending to one feature at a time, children are less likely to control one variable at a time than adults.
And, like the scientific method, the decision-making process I describe in the following sections is cyclical: the data teachers gather through the process are continually used to inform subsequent instruction. These new tools, which consist mainly of standardized test and other assessment results, provide an additional source of information upon which teachers can base curricular and instructional decisions. Ideally, experimentation should produce evidence or observations that are interpretable in order to make the process of evidence evaluation uncomplicated. As a result, the notion of data-driven decision making has steadily gained credence, and it has become crucial for classroom teachers and building-level administrators to understand how to make data-driven educational decisions. In this case we call the statement a generalizing hypothesis. They may in fact be doing discovery science, be testing a model, or pursuing an engineering goal.
Children rarely reviewed their notes, which typically consisted of conclusions, but not the variables used or the outcomes of the experimental tests i. The train was in reality controlled by a secret switch, so that the discovery of the correct solution was postponed until all 16 combinations were generated. The problem with relying solely on the old tools as the basis for instructional decision making is that they do not add up to a systematic process Mertler, Identifying empirical evidence Identifying empirical evidence in another researcher's experiments can sometimes be difficult. In the past, however, the sources of that assessment information were different; instructional decisions were more often based on what I refer to as the "old tools" of the professional educator: intuition, teaching philosophy, and personal experience. Although over-interpreting results does not guarantee erroneous decision making, it is certainly more likely to result in flawed, inaccurate, or less-valid instructional decisions.
The American Biology Teacher
Scientific investigation, broadly defined, includes numerous procedural and conceptual activities, such as asking questions, hypothesizing, designing experiments, making predictions, using apparatus, observing, measuring, being concerned with accuracy, precision, and error, recording and interpreting data, consulting data records, evaluating evidence, verification, reacting to contradictions or anomalous data, presenting and assessing arguments, constructing explanations to oneself and others , constructing various representations of the data graphs, maps, three-dimensional models , coordinating theory and evidence, performing statistical calculations, making inferences, and formulating and revising theories or models e. The independent variable is what you are controlling or changing. For example, building on the research tradition of Piaget e.
When the children were working as engineers, their goal was optimization, that is, to produce a desired effect i. How could you design an experiment to test this hypothesis? Explanatory Hypothesis 1: Birds and insects respond to the same environmental cues, mostly temperature. Requirements for a Testable Hypothesis In order to be considered testable, two criteria must be met: It must be possible to prove that the hypothesis is true.
Children may differentially record the results of experiments, depending on familiarity or strength of prior theories. So, as long as a scientific law can be tested using experiments or observations, it is considered an empirical law. Across this same period, the psychological study of science has evolved from a focus on scientific reasoning as a highly developed form of logical thinking that cuts across scientific domains to the study of scientific thinking as the interplay of general reasoning strategies, knowledge of the natural phenomena being studied, and a sense of how scientific evidence and explanations are generated. For example, distinguishing between theory and evidence and many aspects of modeling do not emerge without explicit instruction and opportunities for practice.